Wireless sensor networks are known in the field of computing. Such networks are used for detecting, monitoring, recording, and reporting signal changes specific to the application in which it is used. For example, in a physiological health monitoring application, a wireless sensor network may include accelerometer sensors for measuring motion and orientation; temperature and humidity sensors; electrodes and bio-amplifiers for measuring heart waveforms, respiration, and muscle activity; oxygen saturation (SPO2) sensors; and galvanic skin response (GSR) sensors.
Wireless sensor networks are composed of one or more sensor nodes and a system controller. Sensor nodes include a computing platform with wireless communication capabilities and one or more sensor devices. The system controller provides a data sync point for the collection and extraction of data, system configuration capabilities, and may include an interface for the end user of the wireless sensor network. The system controller may be referred to as a personal server, network coordinator, or personal area network (PAN) coordinator. The system controller may provide visual, audible or other signals to the user in response to certain events.
“Events” refer to specific changes in signals such as heartbeat detection and health monitoring applications, temperature detection and environmental monitoring, or vibration at specified frequencies in industrial applications. Events can also be used to describe and extract complex features which require combining and analyzing results from multiple signals and sensors.
In resource constrained systems such as wireless sensor networks, nodes are battery powered, placing a premium on low power consumption. Furthermore, such nodes are often manufactured with unique identifiers, making placement of such nodes throughout the network in its desired application critical to its proper function in the system. Furthermore, a wireless sensor network may contain a plurality of sensor nodes, each producing various types of data, each requiring a different amount of power consumption and memory, and any of which may be important to the overall understanding of the system in which it is operating.
Prior art wireless sensor networks rely on complex central monitoring units and require complex signal processing in order to effectively manage data generated by the sensor nodes. It is desirable, therefore, to provide a wireless sensor network capable of reserving memory, controlling the delivery of contextual event data, and allowing for node discovery, configuration, and calibration in multi-node applications. Each of these capabilities is provided in the present invention.